Select appropriate GenAI-resilient assessment methods, classify assessments as authentic or traditional, and identify missing elements that would increase resilience to AI.

Key Topics:

1. Selecting appropriate GenAI-resilient assessment methods for postgraduate research proposals. 
2. Determining most resilient assessment types (oral defense, iterative presentation, public critique). 
3. Classifying assessment types as ‘Authentic’ (real-world application) or ‘Traditional’ (academic format). 
4. Identifying key elements missing from traditional essay assessments. 
5. Determining additions that make assessments GenAI-resilient (personalized data sets, required reflection on AI use). 

Match GenAI-assisted learning activities to pedagogical models, select effective faculty-led tasks for promoting pluralism, and determine GenAI’s core scaffolding function. 

Key Topics:

1. Matching GenAI-assisted learning activities to pedagogical models they support. 
2. Identifying Problem-Based Learning activities where AI generates scenarios. 
3. Selecting effective faculty-led tasks using GenAI to promote diversity and pluralism. 
4. Determining activities that promote comparison and critique of multiple viewpoints. 
5. Determining GenAI’s core function in scaffolding student learning (providing structured feedback, generating outlines). 

Identify challenging phases for monitoring ethical GenAI use, classify research applications requiring oversight, and select primary human skills supervisors should develop.

Key Topics:

1. Identifying critical steps in postgraduate thesis process where ethical GenAI use is most challenging to monitor. 
2. Determining most challenging phases (initial literature review, final discussion writing). 
3. Classifying GenAI research applications as ‘ethical’ or ‘requires significant human oversight’. 
4. Evaluating student use of GenAI for generating methodology sections. 
5. Selecting primary human skills supervisors should develop (critical interpretation of results/assumptions).